This Week in AI：智能体改写安全与商业规则

AI agents dominated the news this week, from security exploits that unfolded in hours to new tools that let agents shop, manage transactions, and conduct scientific research. On the latest episode of This Week in AI, host Vicki Reyzelman of Akamai examined how these developments are testing existing security practices and creating new opportunities for businesses and researchers.

AI attacks are outpacing traditional security responses

AI is changing how attackers find and exploit vulnerabilities. A supply chain attack involving ARTEX, an open source agentic AI penetration-testing framework, helped attackers reach more than 2,250 Microsoft 365 tenants through a ConnectWise compromise. The incident raised concerns about OAuth authentication and the limitations of conventional identity protections when autonomous agents interact with enterprise systems.

A more immediate threat came from PHP2Shell, two vulnerabilities rated 9.2 on the CVSS severity scale that could allow attackers to execute code on vulnerable web servers without authentication. CISA urged immediate patching following the October 21 disclosure. Researchers also documented attackers using AI agents to obtain password hashes and MFA secrets from a European government system within two hours. The speed of exploitation leaves organizations little time to investigate threats before responding, especially smaller businesses with limited security resources.

Security teams can no longer rely on manual review alone. They need automated detection and response, tighter access controls, and network segmentation to limit what compromised agents can reach. But monitoring autonomous agents is challenging. Researchers from METR and Redwood Research identified weaknesses in an earlier version of OpenAI’s internal monitoring system, including one that could allow hundreds of agent actions to be concealed. OpenAI says it has patched vulnerabilities affecting production safeguards, although the researchers haven’t independently evaluated those changes.

The debate over AI safety is also extending beyond technical safeguards. Anthropic proposed federal AI safety legislation, while Google DeepMind employees resigned over the company’s military AI work. Both developments illustrate the growing pressure on AI companies to establish clearer rules for how their technology is developed and used.

The transition to agents brings new challenges

Retailers are taking different approaches to autonomous shopping. Walmart introduced an Agent Gateway that lets approved agents shop within customer-defined spending limits and approval requirements. Amazon has restricted some third-party shopping agents, while banks including Morgan Stanley and Bank of America are limiting agent access to customer accounts. The disagreement goes beyond security. Retailers that depend on advertising and product recommendations have an incentive to keep shoppers on their websites. As more purchases begin with agents, companies will have to reconsider how they maintain customer relationships.

Anthropic is testing a different approach to agent oversight. Claude’s auto mode is becoming the default for Pro, Max, and Team users, allowing automated checks to approve routine actions and block risky ones. Anthropic also contributed its Agent Skills format to the Agentic AI Foundation under the Linux Foundation. More than 70 platforms have adopted the standard, with over a million skills published. Shared formats could make workflows easier to reuse across products, although organizations still need to control which actions those workflows can perform.

Growing agent use also requires more computing capacity and electricity. We discussed NVIDIA’s $164.5 billion in commitments and guarantees supporting AI data centers, including an Ohio campus that SB Energy is building for OpenAI. Power shortages have delayed other projects, including a proposed data center in Essex, where grid operators couldn’t promise adequate electricity until the 2030s. Meanwhile, Amazon is backing a 960-megawatt nuclear project, and Brookfield and NextEra are pursuing a $100 billion AI hub at a former nuclear site in Kentucky. However, money and chips alone can’t solve AI’s infrastructure constraints when electricity generation and grid capacity take years to expand.

AI is accelerating discovery, but validation still takes time

Healthcare offered a more encouraging view of AI’s capabilities. A study of Microsoft’s MAI Diagnostic Orchestrator found that it correctly diagnosed 83.2% of difficult medical cases, compared with 36.1% for generalist physicians. The comparison didn’t include specialists, and the system still needs clinical validation. The research nevertheless suggests AI could help physicians investigate difficult cases and identify conditions they might otherwise miss.

Drug discovery could also benefit from more capable agents. OpenAI announced its acquisition of Orchestra Bio, a platform that coordinates drug development workflows, with plans to integrate it with Rosalind, its life sciences research tools. The combination could help researchers manage experiments and collaborate more efficiently during a development process that typically takes 10 to 15 years from initial discovery to approval.

An Anthropic protein-design experiment provided a concrete example of faster early-stage research. In 64 hours, an Anthropic model generated 318,484 candidate protein designs targeting scorpion venom. Researchers from Adaptyv Bio and Twist Bioscience subsequently tested 211 designs and identified 17 that bound to toxins. The researchers haven’t established whether those proteins can neutralize venom, but the experiment showed how AI can rapidly narrow a vast search space before scientists begin more expensive laboratory testing.

What’s next

We’ll be back on Monday, November 2, for another episode covering the latest developments in AI research and applications. You can catch previous episodes on YouTube, Spotify, Apple, or wherever you get your podcasts.